Economists who use survey or administrative data for inferences regarding a population
may want to combine information obtained from two or more samples drawn from the …

The overall objectives of this review and synthesis are to study the basics of information-
theoretic methods in econometrics, to examine the connecting theme among these methods …

There are many settings where researchers are interested in estimating average treatment
effects and are willing to rely on the unconfoundedness assumption, which requires that the …

The propensity score plays a central role in a variety of causal inference settings. In
particular, matching and weighting methods based on the estimated propensity score have …

This paper proposes entropy balancing, a data preprocessing method to achieve covariate
balance in observational studies with binary treatments. Entropy balancing relies on a …

We are interested in estimating the average effect of a binary treatment on a scalar outcome.
If assignment to the treatment is exogenous or unconfounded, that is, independent of the …

Abstract “Site selection bias” can occur when the probability that a program is adopted or
evaluated is correlated with its impacts. I test for site selection bias in the context of the …

The estimation of average treatment effects based on observational data is extremely
important in practice and has been studied by generations of statisticians under different …

Randomized controlled trials (RCTs) can provide unbiased estimates of sample average
treatment effects. However, a common concern is that RCTs may fail to provide unbiased …

Poverty maps provide information on the spatial distribution of living standards. They are an
important tool for policymakers, who rely on them to allocate transfers and inform policy …